First came the Nature vs. Nurture debate: what makes us who we are? Is it nature — what our parents, at the moment of conception, brought to the genealogical table (or, bed, for those of us with more traditional parents)? Or is it where we lived and how those parents treated us in our early years and beyond? Then came the Taste Great, Less Filling conundrum. Today, at least in the web universe, rages the human versus machine controversy. At its core, the questions is: what returns the best, most relevant results (search results, relevant news, etc.)? Machine-generated algorithms or human “editors”? Google, with its mysterious search algorithms and millions of servers, is the poster-child for the “Machine” camp (although the reality is that their algorithms rely on human editors). In the “Wisdom of the Crowd” camp are the Web 2.0 likes of Digg, Wikipedia and del.icio.us. Like in the early days of the Nature vs. Nurture debate, (or Taste Great, Less Filling, for that matter) people are polarized over the issue — as if it’s one or the other. John Battelle sparked another round of debate on the matter just last week. Of course, the right answer is “both”.

Machines can do things that humans just can’t do very efficiently. They can process huge amounts of data very quickly (like the massive amounts of consumer-generated media that exist) . And machines don’t need to sleep or take latte breaks, so they can monitor things around the clock, in real-time. Of course, the categorizations and the kinds of processing that machines can do are very “gross” — they can count things, extract links, and look for patterns and run analyses that humans devise (like, say, an Influence algorithm or a Significance algorithm or patterns in language to determine sentiment). Machines can also count, measure and incorporate HUMAN (user) actions and behaviors — both explicit and implicit — along with the technical data, and that’s where the lines begin to blur and where things get interesting. So, we desperately need smart machines, directed by far-smarter humans, for complex things things like search or monitoring the voice of the customer out across the Internet.

But people, especially teams of like-minded people with a common purpose, can do what no machine could ever do — draw conclusions, add insight and strategize. Humans can add the “so what”. A founding belief of Scout Labs is “Let technology do what it does best, and people do what we do best. Together, we’re a pretty good team.” We have architected the service to offer the best of both worlds, working together seamlessly. Of course all this is a means to an end. Our users just want to know what stuff she needs to pay attention to right now and to collaborate with her team to do something about it. We are excited that very soon, everyone will get a chance to use Scout Labs and see Man and Machine working together in peace and harmony. Taste Great vs. Less Filling will still be there to fight about.